First chapter of Kernighan and Donovan's new Go book [pdf]

Re:First chapter of Kernighan and Donovan's new Go book [pdf] by danieldk on Monday October 19, 2015 @02:16PM (#10414581)

Everything I used to use Python for, I can do faster in Go. The notable exception to this is statistical analysis, as Go does not have any FORTRAN bindings, whereas Python does (through Numpy & co.).

golang does have BLAS bindings through gonum:

https://godoc.org/github.com/gonum/blas/cgo

Coming back to the main question. I use Go as my primary language these days. E.g., my dependency parser and neural net dependency parser (which uses the aforementioned BLAS binding) are written in Go:

https://github.com/danieldk/dpar https://github.com/danieldk/dparnn

What I like about Go: it's C-like without the unsafety of C nor the complexity of C++. Moreover, I've found that working in Go is generally as productive as Python (short compile times, good tooling, completion in vim, lightweight package system), while being much faster and better-fit for large projects.

What I dislike about Go: it's a cliché, but the lack of parametric polymorphism is jarring.

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Re:First chapter of Kernighan and Donovan's new Go book [pdf] by howeman on Monday October 19, 2015 @03:00PM (#10414852)

gonum also has LAPACK bindings

godoc.org/github.com/gonum/lapack/cgo

Assuming you need float64, BLAS and LAPACK are most easily accessed through the wrapper packages godoc.org/github.com/gonum/blas/blas64 and godoc.org/github.com/gonum/lapack/lapack64. This way code can be written to either use the native go implementations or the assembly/c/fortran ones.

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